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A simple step_info and stepinfo (for matlab compatibility) was implemented.
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Lines changed: 194 additions & 2 deletions

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‎control/matlab/timeresp.py‎

Lines changed: 46 additions & 1 deletion
Original file line numberDiff line numberDiff line change
@@ -4,7 +4,7 @@
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Note that the return arguments are different than in the standard control package.
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"""
66

7-
__all__ = ['step', 'impulse', 'initial', 'lsim']
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__all__ = ['step', 'stepinfo', 'impulse', 'initial', 'lsim']
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def step(sys, T=None, X0=0., input=0, output=None, return_x=False):
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'''
@@ -66,6 +66,51 @@ def step(sys, T=None, X0=0., input=0, output=None, return_x=False):
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6767
return yout, T
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69+
def stepinfo(sys, T=None, SettlingTimeThreshold=0.02, RiseTimeLimits=(0.1,0.9)):
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'''
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Step response characteristics (Rise time, Settling Time, Peak and others).
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Parameters
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----------
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sys: StateSpace, or TransferFunction
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LTI system to simulate
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T: array-like object, optional
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Time vector (argument is autocomputed if not given)
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SettlingTimeThreshold: float value, optional
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Defines the error to compute settling time (default = 0.02)
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RiseTimeLimits: tuple (lower_threshold, upper_theshold)
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Defines the lower and upper threshold for RiseTime computation
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Returns
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-------
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S: a dictionary containing:
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RiseTime: Time from 10% to 90% of the steady-state value.
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SettlingTime: Time to enter inside a default error of 2%
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SettlingMin: Minimum value after RiseTime
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SettlingMax: Maximum value after RiseTime
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Overshoot: Percentage of the Peak relative to steady value
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Undershoot: Percentage of undershoot
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Peak: Absolute peak value
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PeakTime: time of the Peak
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See Also
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--------
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step, lsim, initial, impulse
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Examples
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--------
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>>> S = stepinfo(sys, T)
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'''
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from ..timeresp import step_info
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S = step_info(sys, T, SettlingTimeThreshold, RiseTimeLimits)
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return S
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69114
def impulse(sys, T=None, X0=0., input=0, output=None, return_x=False):
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'''
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Impulse response of a linear system

‎control/tests/timeresp_test.py‎

Lines changed: 55 additions & 0 deletions
Original file line numberDiff line numberDiff line change
@@ -87,6 +87,61 @@ def test_step_response(self):
8787
np.testing.assert_array_equal(Tc.shape, Td.shape)
8888
np.testing.assert_array_equal(youtc.shape, youtd.shape)
8989

90+
def test_step_info(self):
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# From matlab docs:
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sys = TransferFunction([1,5,5],[1,1.65,5,6.5,2])
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Strue = {
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'RiseTime': 3.8456,
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'SettlingTime': 27.9762,
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'SettlingMin': 2.0689,
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'SettlingMax': 2.6873,
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'Overshoot': 7.4915,
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'Undershoot': 0,
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'Peak': 2.6873,
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'PeakTime': 8.0530
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}
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S = step_info(sys)
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# Very arbitrary tolerance because I don't know if the
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# response from the MATLAB is really that accurate.
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# maybe it is a good idea to change the Strue to match
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# but I didn't do it because I don't know if it is
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# accurate either...
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rtol = 2e-2
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np.testing.assert_allclose(
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S.get('RiseTime'),
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Strue.get('RiseTime'),
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rtol=rtol)
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np.testing.assert_allclose(
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S.get('SettlingTime'),
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Strue.get('SettlingTime'),
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rtol=rtol)
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np.testing.assert_allclose(
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S.get('SettlingMin'),
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Strue.get('SettlingMin'),
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rtol=rtol)
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np.testing.assert_allclose(
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S.get('SettlingMax'),
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Strue.get('SettlingMax'),
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rtol=rtol)
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np.testing.assert_allclose(
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S.get('Overshoot'),
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Strue.get('Overshoot'),
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rtol=rtol)
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np.testing.assert_allclose(
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S.get('Undershoot'),
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Strue.get('Undershoot'),
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rtol=rtol)
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np.testing.assert_allclose(
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S.get('Peak'),
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Strue.get('Peak'),
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rtol=rtol)
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np.testing.assert_allclose(
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S.get('PeakTime'),
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Strue.get('PeakTime'),
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rtol=rtol)
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90145
def test_impulse_response(self):
91146
# Test SISO system
92147
sys = self.siso_ss1

‎control/timeresp.py‎

Lines changed: 93 additions & 1 deletion
Original file line numberDiff line numberDiff line change
@@ -58,7 +58,7 @@
5858
from .statesp import _convertToStateSpace, _mimo2simo, _mimo2siso
5959
from .lti import isdtime, isctime
6060

61-
__all__ = ['forced_response', 'step_response', 'initial_response',
61+
__all__ = ['forced_response', 'step_response', 'step_info', 'initial_response',
6262
'impulse_response']
6363

6464
# Helper function for checking array-like parameters
@@ -432,6 +432,98 @@ def step_response(sys, T=None, X0=0., input=None, output=None,
432432

433433
return T, yout
434434

435+
def step_info(sys, T=None, SettlingTimeThreshold=0.02, RiseTimeLimits=(0.1,0.9)):
436+
'''
437+
Step response characteristics (Rise time, Settling Time, Peak and others).
438+
439+
Parameters
440+
----------
441+
sys: StateSpace, or TransferFunction
442+
LTI system to simulate
443+
444+
T: array-like object, optional
445+
Time vector (argument is autocomputed if not given)
446+
447+
SettlingTimeThreshold: float value, optional
448+
Defines the error to compute settling time (default = 0.02)
449+
450+
RiseTimeLimits: tuple (lower_threshold, upper_theshold)
451+
Defines the lower and upper threshold for RiseTime computation
452+
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Returns
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-------
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S: a dictionary containing:
456+
RiseTime: Time from 10% to 90% of the steady-state value.
457+
SettlingTime: Time to enter inside a default error of 2%
458+
SettlingMin: Minimum value after RiseTime
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SettlingMax: Maximum value after RiseTime
460+
Overshoot: Percentage of the Peak relative to steady value
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Undershoot: Percentage of undershoot
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Peak: Absolute peak value
463+
PeakTime: time of the Peak
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SteadyStateValue: Steady-state value
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See Also
468+
--------
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step, lsim, initial, impulse
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Examples
472+
--------
473+
>>> info = step_info(sys, T)
474+
'''
475+
sys = _get_ss_simo(sys)
476+
if T is None:
477+
if isctime(sys):
478+
T = _default_response_times(sys.A, 1000)
479+
else:
480+
# For discrete time, use integers
481+
tvec = _default_response_times(sys.A, 1000)
482+
T = range(int(np.ceil(max(tvec))))
483+
484+
T, yout = step_response(sys, T)
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486+
# Steady state value
487+
InfValue = yout[-1]
488+
489+
# RiseTime
490+
tr_lower_index = (np.where(yout >= RiseTimeLimits[0] * InfValue)[0])[0]
491+
tr_upper_index = (np.where(yout >= RiseTimeLimits[1] * InfValue)[0])[0]
492+
RiseTime = T[tr_upper_index] - T[tr_lower_index]
493+
494+
# SettlingTime
495+
sup_margin = (1. + SettlingTimeThreshold) * InfValue
496+
inf_margin = (1. - SettlingTimeThreshold) * InfValue
497+
# find Steady State looking for the first point out of specified limits
498+
for i in reversed(range(T.size)):
499+
if((yout[i] <= inf_margin) | (yout[i] >= sup_margin)):
500+
SettlingTime = T[i + 1]
501+
break
502+
503+
# Peak
504+
PeakIndex = np.abs(yout).argmax()
505+
PeakValue = yout[PeakIndex]
506+
PeakTime = T[PeakIndex]
507+
SettlingMax = (yout).max()
508+
SettlingMin = (yout[tr_upper_index:]).min()
509+
# I'm really not very confident about UnderShoot:
510+
UnderShoot = yout.min()
511+
OverShoot = 100. * (yout.max() - InfValue) / (InfValue - yout[0])
512+
513+
# Return as a dictionary
514+
S = {
515+
'RiseTime': RiseTime,
516+
'SettlingTime': SettlingTime,
517+
'SettlingMin': SettlingMin,
518+
'SettlingMax': SettlingMax,
519+
'Overshoot': OverShoot,
520+
'Undershoot': UnderShoot,
521+
'Peak': PeakValue,
522+
'PeakTime': PeakTime,
523+
'SteadyStateValue': InfValue
524+
}
525+
526+
return S
435527

436528
def initial_response(sys, T=None, X0=0., input=0, output=None,
437529
transpose=False, return_x=False):

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